globe$dt <- as.Date(globe$dt, format = "%Y-%m-%d")
globe$year <- as.numeric(format(globe$dt, "%Y"))
globe$month <- as.numeric(format(globe$dt,"%m"))
globe$month_text <- month.abb[globe$month]
globe[,c(10,11,12)]## year month month_text
## 1: 1750 1 Jan
## 2: 1750 2 Feb
## 3: 1750 3 Mar
## 4: 1750 4 Apr
## 5: 1750 5 May
## ---
## 3188: 2015 8 Aug
## 3189: 2015 9 Sep
## 3190: 2015 10 Oct
## 3191: 2015 11 Nov
## 3192: 2015 12 Dec
## `geom_smooth()` using method = 'loess'
## # A tibble: 6 x 2
## Year Temp
## <int> <dbl>
## 1 1851 10.4
## 2 1852 10.0
## 3 1853 10.4
## 4 1854 10.8
## 5 1855 10.6
## 6 1856 9.49
## `geom_smooth()` using method = 'loess'
data_general <- us_state_data[,c(1,4,6)]
data_general <- data_general %>%
group_by(Year,State) %>%
summarise(value=mean(AverageTemperature))
colnames(data_general)[2]<- "region"
data_general$region<-tolower(data_general$region)
data_2013 <- data_general %>%
filter(Year==2013)
data_2013<-data_2013[,2:3]
data_1850 <- data_general %>%
filter(Year==1850)
data_1850<-data_1850[,2:3]print(state_choropleth(data_1850,
title="Land Temperature 1850",
num_colors = 8,
legend="Degrees"),reference_map=TRUE)print(state_choropleth(data_2013,
title="Land Temperature 2013",
num_colors = 8,
legend="Degrees"),reference_map=TRUE)globe_2 <- globe_1[, lapply(.SD, mean),by=year, .SDcols= c("LandAverageTemperature","LandMaxTemperature","LandMinTemperature","LandAndOceanAverageTemperature","LandAndOceanAverageTemperatureUncertainty","LandAverageTemperatureUncertainty","LandMaxTemperatureUncertainty","LandMinTemperatureUncertainty")]
head(globe_2)## year LandAverageTemperature LandMaxTemperature LandMinTemperature
## 1: 1850 7.900667 13.47667 1.964333
## 2: 1851 8.178583 13.08100 2.203917
## 3: 1852 8.100167 13.39733 2.337000
## 4: 1853 8.041833 13.88658 1.892500
## 5: 1854 8.210500 13.97742 1.762167
## 6: 1855 8.110750 13.49317 1.702833
## LandAndOceanAverageTemperature
## 1: 14.86717
## 2: 14.99183
## 3: 15.00650
## 4: 14.95517
## 5: 14.99100
## 6: 15.02108
## LandAndOceanAverageTemperatureUncertainty
## 1: 0.3081667
## 2: 0.3120833
## 3: 0.3164167
## 4: 0.2838333
## 5: 0.2764167
## 6: 0.2911667
## LandAverageTemperatureUncertainty LandMaxTemperatureUncertainty
## 1: 0.8764167 2.394833
## 2: 0.8819167 2.397250
## 3: 0.9182500 2.619250
## 4: 0.8350000 2.095083
## 5: 0.8256667 1.783333
## 6: 0.8871667 1.331417
## LandMinTemperatureUncertainty
## 1: 1.571167
## 2: 1.632417
## 3: 1.382917
## 4: 1.355583
## 5: 1.357000
## 6: 1.655333